News Feed March April 2023

Published papers

  • Haonan Zhong, Jiamin Chang, Ziyue Yang, Tingmin Wu, Pathum Chamikara  Mahawaga Arachchige, Chehara Pathmabandu, and Minhui Xue. 2023. Copyright Protection and Accountability of Generative AI: Attack, Watermarking and Attribution. In Companion Proceedings of the ACM Web Conference 2023 (WWW ’23 Companion), April 30-May 4, 2023, Austin, TX, USA. ACM, New York, NY, USA, 5 pages. This paper proposes an evaluation framework to provide a comprehensive overview of the current state of the copyright protection measures for GANs, evaluate their performance across a diverse range of GAN architectures, and identify the factors that affect their performance and future research directions.
  • Farina Riaz, Shahab Abdulla, Hajime Suzuki , Srinjoy Ganguly, Ravinesh C. Deo, and Susan Hopkins, “Accurate image multi-class classification neural network model with quantum entanglement approach,” Sensors (Impact Factor 3.85), March 2023. 11 pages. This is the first paper published from the new Quantum ML for Cyber project.  In this paper, we propose a novel neural network with quantum entanglement method to enhance the accuracy of image classification.  We show the improvements in image classification accuracy over 10 class hand written digits and photos but not over 43 class real-life traffic signs. Exact causes of the improvement and degradation are currently open questions and requiring further investigation.
  • Chehara Pathmabandu, John Grundy, Mohan Baruwal Chhetri, Zubair Baig, Privacy for IoT: Informed consent management in Smart Buildings, Future Generation Computer Systems, Volume 145, 2023, Pages 367-383, The impact factor of this venue is quite high – It’s 7.18. Link: ( The paper proposes a novel Informed Consent Management Engine (ICME) to handle the tension between personal data disclosure and convenience in shared smart spaces, accompanied by a rigorous evaluation. The main objective of our study is to design an appropriate mechanism for Smart Building consent management comprising a generalised reference architecture and to instantiate a comprehensive framework for user consent management in Smart Buildings to mitigate the privacy paradox. We also highlight in our work; the observation of perceived usefulness, benefits, challenges of the solution, and impact on the environment/SB stakeholders.
  • Josef Pieprzyk, Jarek Duda, Marcin Pawłowski, Seyit Camtepe, Arash Mahboubi and Paweł Morawiecki, The Compression Optimality of Asymmetric Numeral Systems, Entropy, MDPI, 2023, 25, 672. Asymmetric Numeral System (ANS) is a compression algorithm invented by Jarek Duda in 2009, which has taken the IT industry by storm. The paper investigates compression rate of ANS. It turns out that the main component of ANS is its symbol spread, which can be chosen arbitrarily. However, for each symbol spread ANS has a slightly different compression rate. The paper gives an algorithm that maximizes the compression rate.

Publications accepted

  • Baiqi Chen, Tingmin Wu, Yanjun Zhang (Deakin University), Mohan Baruwal Chhetri, Guangdong Bai (University of Queensland). Investigating Users’ Understanding of Privacy Policies of Virtual Personal Assistant Applications. Accepted at AsiaCCS 2023. The paper presents the results of a subjective study to investigate the level of users’ understanding of privacy policies, targeting VPA apps of Amazon skills. The study focussed on users’ understanding of technical terms in privacy policies and the role of explanations in improving users’ understanding. 
  • Mengyao Ma, Yanjun Zhang (Deakin University), Leo Yu Zhang (Deakin University), M.A.P. Chamikara, Mohan Baruwal Chhetri, Guangdong Bai (University of Queensland). LoDen: Making Every Client in Federated Learning a Defender Against the Poisoning Membership Inference Attacks. Accepted at AsiaCCS 2023. The paper proposes a novel client-side defence mechanism against poisoning membership inference attacks in federated learning by leveraging access to own datasets to detect suspicious privacy attacks against samples and remove the ones under attack. 
  • Geetanjli Sharma, M.A.P. Chamikara, Mohan Baruwal Chhetri, Yi-Ping Phoebe Chen (La Trobe University). SoK: Systematising Attack Studies in Federated Learning – From Sparseness to Completeness. Accepted at AsiaCCS 2023. The paper uses a causal model inspired by structural equation modelling to systematise the existing literature on FL attack studies. 
  • Mohan Baruwal Chhetri (CSIRO’s Data61), Abdur Rahim Mohammad Forkan (SUT), Quoc Bao Vo (SUT), Surya Nepal (CSIRO’s Data61), Ryszard Kowalczyk (UniSA). Towards Proactive Risk-aware Cloud Cost Optimisation Leveraging Transient Resources. Accepted to IEEE Transactions of Services Computing (Impact Factor: 11.019). The paper proposes an approach for risk-aware cloud cost optimisation that is inspired by the concept of portfolio diversification. Contract diversification mitigates the resource revocation risk by procuring the required compute capacity as a mixed portfolio of transient and non-transient resources. Resource diversification further diversifies the risk by using multiple transient resource types. 
  • Sanath Kahagalage (UNSW), Hasan Hüseyin Turan (UNSW) Fatemeh Jalalvand (CSIRO’s Data61), Sondoss El Sawah (UNSW). A novel graph-theoretical clustering approach to find a reduced set with extreme solutions of Pareto optimal solutions for multi-objective optimization problems. Accepted to Journal of Global Optimization, 2023 (journal ranking: A). This paper proposes a novel graph-theoretical clustering method to identify representative solutions of a large number of Pareto optimal solutions obtained from multi-objective optimisation problems. The identified representative solutions help decision makers to select suitable solutions among the large set of Pareto optimal solutions, which are all optimal with some trade-offs. The proposed method outperforms the traditional clustering approaches in Pareto pruning like K-means clustering.

  • Mohamed Ahzam Amanullah (Deakin), Seng Loke (Deakin), Mohan Baruwal Chhetri, Robin Doss (Deakin). A Taxonomy and Analysis of Misbehaviour Detection in Cooperative Intelligent Transport Systems: A Systematic Review. Accepted at ACM Computing Surveys (CORE A*). This paper proposes a thematic taxonomy on misbehaviour detection in cooperative intelligent transport systems (C-ITS) based on a comparative analysis of existing studies (EP2022-3493).
  • Alan Colman, Anton Uzunov, Bao Vo, Mohan Baruwal Chhetri, Agent Controlled Service Meshes for Resilient, Self-Adaptive Microservice Systems. Accepted at IEEE International Conference on Software Services Engineering (SSE 2023). The paper proposes an agent-oriented architectural approach for creating resilient, self-managing microservice-based systems (EP2023-1175).
  • Saad Hashmi, Hoa Khanh Dam, Anton Uzunov, Mohan Baruwal Chhetri, Aditya Ghose, Alan Colman. Goal-Driven Adversarial Search for Distributed Self-Adaptive Systems. Accepted at IEEE International Conference on Software Services Engineering (SSE 2023). This paper proposes a novel approach for distributed, multi-agent-based adversarial self-exploration for realising resilience and antifragility in contested environments (EP2023-1176).
  • Hua Ma (UoA, Data61 PhD student), Huming Qiu, Yansong Gao, Zhi Zhang, Sharif Abuadbba, Minhui Xue, Anmin Fu, Jiliang Zhang, Said F. Al-Sarawi, and Derek Abbott. Quantization backdoors to deep learning commercial frameworks. Accepted by IEEE Transactions on Dependable and Secure Computing (IEEE TDSC 2023) (Target venue, CORE A). This work reveals the backdoor vulnerability when commercial quantization frameworks including TensorFlow-Lite and Pytorch Mobile are used to convert a full-precision deep learning model into int-8 model to fit IoT/Mobile device applications. (EP2023-1762)
  • Jiliang Zhang, Shuang Peng, Yansong Gao, Zhi Zhang, and Qinghui Hong. APMSA: Adversarial Perturbation Against Model Stealing Attacks. Accepted by IEEE Transactions on Information Forensics and Security (IEEE TIFS 2023) (Target venue, CORE A). This work turns adversarial perturbation on querying input as a defense to harden the model stealing attacks from the perspective of forcing more querying budgets being used. (EP2023-1451) 
  • Ngoc Duy, Pham (Latrobe Univeristy), Sharif Abuadbba, Yansong Gao, Tran Khoa Phan, and Naveen Chilamkurti. Binarizing split learning for data privacy enhancement and computation reduction. Accepted by IEEE Transactions on Information Forensics and Security (IEEE TIFS 2023) (Target venue, CORE A). This work reduces the computation/communication overhead to the device-side and concurrently enhances the data security and privacy in Split Learning through binarization. (EP2023-1794)
  • Muhammed F. Esgin, Oguzhan Ersoy, Veronika Kuchta, Julian Loss, Amin Sakzad, Ron Steinfeld, Wayne Yang, Raymond K. Zhao, A New Look at Blockchain Leader Election: Simple, Efficient, Sustainable and Post-Quantum, Accepted., 18th ACM ASIA Conference on Computer and Communications Security (ACM ASIACCS 2023). CORE Ranking A., Our paper proposes a simple, efficient, and quantum-safe novel solution for the core functionality of the leader election protocol used by blockchain applications such as the Algorand. Our techniques can help the migration to quantum-safe in Algorand-like blockchain applications with little extra overhead. E-publish number: EP2023-1291
  • Ruoxi Sun, Minhui Xue, Gareth Tyson, Tian Dong, Shaofeng Li, Shuo Wang, Haojin Zhu, Seyit Camtepe, and Surya Nepal, Mate! Are You Really Aware? An Explainability-Guided Testing Framework for Robustness of Malware Detectors, Accepted, The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE, CORE A*), In this work, we propose an explainability-guided and model-agnostic testing framework for robustness of malware detectors when confronted with adversarial attacks. According to our findings, we suggest that machine learning-based antivirus products should consider adopt the proposed approach to enhance their robustness. We believe that exploring this aspect further could prompt a new approach to defending against malware evasion attacks. Our findings shed light on the limitations of current malware detectors, as well as how they can be improved. Future collaboration with security experts from the industry is feasible. E-publish number: EP2023-1326
  • Ruoxi Sun, Minhui Xue, Gareth Tyson, Shuo Wang, Seyit Camtepe and Surya Nepal, Not Seen, Not Heard in the Digital World! Measuring Privacy Practices in Children’s Apps, Accepted, The Web Conference (WWW, CORE A*), In this paper, we explore the potential privacy issues and threats that exist in children’s mobile apps. Our findings suggest that, despite significant attention to children’s privacy, a large gap between regulatory provisions, app store policies, and actual development practices exist. After we disclosed our findings to the Google privacy team, the Play store updated the FAMILY category requirement and the Families policy. Our research sheds light for government policymakers, app stores, and developers. Collaboration with the Google privacy team could expand this study further.  EP2023-0479

Good news

  • Australia’s National Quantum Strategy. 

National Quantum Strategy, Building a thriving future with Australia’s quantum advantage, industry.Quantum Strategy

Our QTC work is recognised on page 39

  • Garrison Gao is now a Senior Member of IEEE.
  • Staff

    Our group is growing. Since the 1/1/23 we have welcomed:

    • 6 research scientists
    • 5 postdoctoral fellows
    • 4 engineers

    We are committed to ensure our staff Health and Safety. Clayton team doing a Hazard Hunt


    • Mohan Baruwal Chhetri co-presented a talk titled Risk of Quantum Computing to Cybersecurity to the Quantum Technologies FSP/CCC Seminar Series on 28 April 2023. 
    • HCSE&CS 2023 (Human Centric Software Engineering & Cyber Security) – has been accepted at ASE 2023, Mohan Baruwal Chhetri and Marthie Grobler are on the organising committee.
    • M.A. P. Chamikara delivered a talk at the PETS event (PETS Workshop on Current Challenges and Emerging Technologies) in Sydney. During the talk, we covered the broader CRC privacy portfolio – PPTA, PIF, OptimShare, and Trajectory Privacy. 

    • Sharif Abuadbba presented a talk titled “DOITrust: Dissecting On-Chain Compromised Internet Domains via Graph Learning.” ECU Seminar Series on 4th of May 2023.
    • Ruoxi Sun attended the WWW’23 at Austin, TX, and gave a 10-minute presentation for our children’s app paper. A poster, “Copyright Protection and Accountability of Generative AI: Attack, Watermarking and Attribution” by Haonan Zhong, Jiamin Chang, Ziyue Yang, Tingmin Wu, Pathum Chamikara Mahawaga Arachchige, Chehara Pathmabandu, and Minhui Xue was exhibited at WWW’23. 

    • Usman Muhammad presented our quantum work to the Aus Army Chief of Staff Lt. Gen. Simon Stuart. This also made to the National Strategy.

    Media Release

    Regular Events

    Data61 has established a new quantum technology program, focused in the areas of quantum software, quantum security, and quantum algorithms & applications. This seminar series will invite quantum experts to provide an updated summary of the global research on the topics of interest, highlight key challenges in the development of quantum technologies and stimulate new ideas for future research directions. The seminar series will also provide engagement and networking opportunities for Data61 researchers. The seminars will be scheduled on the last Wednesday (3-4 PM AEST) of every month.

    In collaboration with Quantum Technology FSP; for more info


    • 6G security seminar series

    This seminar series is part of the 6G Security Research and Development Program conducted on behalf of the Australian Government – Department of Home Affairs. The Program aims to conduct foundational research into the security requirements of 6G technologies, and shape the development of 6G telecommunications standards internationally.

    6g technology background abstract illustration,Computer system and 6G system equipment,3d rendering